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Toxicity data for: COLLEMBOT: AI-based counting of Collembola for OECD 232 Tests

Zenodo (CERN European Organization for Nuclear Research) 2026 Score: 50 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Sam van Loon, Micha Wehrli, Sam van Loon, Sam van Loon, Sam van Loon, Sam van Loon, Sam van Loon, Sam van Loon, Micha Wehrli, Adrian Meyer, Magdalena M. Mair Adrian Meyer, Adrian Meyer, Adrian Meyer, Magdalena M. Mair Sam van Loon, Sam van Loon, Éverton Souza da Silva, Éverton Souza da Silva, Éverton Souza da Silva, Sam van Loon, Éverton Souza da Silva, Sam van Loon, Magdalena M. Mair Sam van Loon, Sam van Loon, Sam van Loon, Magdalena M. Mair Magdalena M. Mair Magdalena M. Mair Magdalena M. Mair Heike Feldhaar, Bart G van Hall, Bart G van Hall, Kees van Gestel, Miriam Langer, Kees van Gestel, Miriam Langer, Kees van Gestel, Miriam Langer, Kees van Gestel, Tiago Natal da Luz, Tiago Natal da Luz, Tiago Natal da Luz, Tiago Natal da Luz, Döring Max, Döring Max, Döring Max, Döring Max, Heike Feldhaar, Heike Feldhaar, Heike Feldhaar, Magdalena M. Mair Heike Feldhaar, Heike Feldhaar, Heike Feldhaar, Magdalena M. Mair Micha Wehrli, Magdalena M. Mair Magdalena M. Mair Denis Jordan, Magdalena M. Mair Denis Jordan, Denis Jordan, Magdalena M. Mair Denis Jordan, Sam van Loon, Miriam Langer, Miriam Langer, Magdalena M. Mair

Summary

This dataset provides raw and processed data from soil toxicity tests comparing manual and automated counting methods for springtails exposed to various contaminants, including polystyrene microplastics. The COLLEMBOT system uses AI-based image analysis to count test organisms, aiming to improve efficiency and reduce human error in standardized ecotoxicological assays. The data support validation of automated approaches for assessing microplastic toxicity in soil organisms.

Polymers

Body Systems

Reproductive

This dataset is part of a scientific article in preparation. Currently submitted to Environmental Toxicology & Chemistry. This dataset contains raw and processed data from laboratory toxicity tests on Folsomia candida (Collembola) exposed to various soil contaminants under controlled conditions. The study compares traditional manual counting of juveniles and adults with automated image-based counting using the COLLEMBOT system. Data were collected across multiple soils (LUFA 2.2, OECD variants) and exposure scenarios, including different concentrations of pesticides (e.g., imidacloprid, chlorpyrifos, lindane), fungicides (fluazinam, cyproconazole), microplastics (polystyrene), and reference substances (boric acid). The dataset includes: Raw observations: survival and reproduction endpoints per replicate. Manual vs automated counts: paired measurements for validation of automated image analysis. Metadata: compound identity, soil type, concentration (nominal and adjusted), replicate information. Dose-response modeling script: ECx values (ED10–ED90), NOEC/LOEC estimates, and statistical comparisons between counting methods. This resource supports ecotoxicological research, automation in soil toxicity testing, and reproducibility in environmental risk assessment workflows. This repository also contains the model weights for COLLEMBOT under a AGPL 3.0 license with the code being available at GitHub under a MIT license: https://github.com/waldstrom/collembot

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